车轮转速信号混合噪声的非线性Volterra滤波方法

发布时间：2018-05-28 04:31

  本文选题：非线性Volterra滤波器 + 车轮转速信号　； 参考：《兰州大学学报(自然科学版)》2017年02期

【摘要】：为保证机车黏着控制品质,提出车轮转速信号所含混合噪声(高斯噪声和冲击噪声)的非线性Volterra滤波方法,并结合混沌优化策略及动态随机局部搜索算子,提出动态随机局部搜索生物地理优化算法对Volterra滤波器模型参数进行优化求解.利用Volterra滤波器的结构优势(具有预测性能、兼具线性和非线性项),既能滤除混合噪声又可满足黏着控制的实时性要求.仿真实验结果表明,经优化求解的非线性Volterra滤波器实现了对车轮转速信号所含混合噪声的有效滤除.
[Abstract]:In order to ensure the quality of locomotive adhesion control, a nonlinear Volterra filtering method for mixed noise (Gao Si noise and shock noise) in wheel speed signal is proposed, which combines chaos optimization strategy and dynamic random local search operator. A dynamic random local search biogeographic optimization algorithm is proposed to optimize the parameters of Volterra filter model. Taking advantage of the structural advantages of Volterra filters (predictive performance, both linear and nonlinear terms), the mixed noise can be filtered and the real-time requirements of adhesive control can be satisfied. The simulation results show that the optimized nonlinear Volterra filter can effectively remove the mixed noise from the wheel speed signal.
【作者单位】： 兰州交通大学机电工程学院;
【基金】：国家自然科学基金项目(51665027,11462011)
【分类号】：TN713;U260
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本文编号：1945307